饮水型砷暴露人群改水前后尿砷甲基化代谢产物水平分析
Analysis of urinary arsenic methylation metabolites in population exposed to arsenic through drinking water before and after water improvement
摘要目的:探讨改水对饮水型砷暴露人群尿砷甲基化代谢的影响。方法:采用整群抽样方法选取内蒙古自治区巴彦淖尔市饮水型地方性砷中毒病区居住年限≥10年的常住居民作为调查对象,分别在2004(改水前)、2014(改水后4年)及2017年(改水后7年)采集调查对象尿样( n = 874、111、145),并于2014、2017年对部分人群进行跟踪随访。采用高效液相色谱电感耦合等离子体质谱仪(HPLC-ICP-MS)检测尿中不同形态砷代谢产物[无机砷(iAs)、一甲基胂(MMA)、二甲基胂(DMA)],计算总砷(tAs)含量、无机砷百分比(iAs%)、一甲基胂百分比(MMA%)、二甲基胂百分比(DMA%)、一甲基化率(PMI)、二甲基化率(SMI)、一甲基胂与二甲基胂比值(MMA/DMA)。对改水前后及改水后不同时间点砷暴露人群尿砷代谢产物含量及分布进行对比分析。 结果:与2004年比较,2014年砷暴露人群尿中iAs、MMA、DMA、tAs、iAs%水平均较低( Z =-14.12、-12.79、-14.27、-14.21、-6.90, P均< 0.001),MMA%、DMA%、PMI水平均较高( Z =-3.22、-2.91、-6.90, P均< 0.05);同一砷暴露人群与2004年比较,2014年( n = 48)尿中iAs、MMA、DMA、tAs、iAs%水平均较低( Z =-5.57、-5.53、-5.54、-5.55、-2.86, P均< 0.05),PMI水平较高( Z =-2.86, P = 0.004)。与2014年比较,2017年砷暴露人群尿中iAs%和MMA/DMA水平均较低( Z =-4.97、-2.25, P均< 0.05),MMA、DMA、tAs、DMA%、PMI、SMI水平均较高( Z =-4.01、-5.39、-4.77、-4.61、-4.97、-2.25, P均< 0.05);同一砷暴露人群与2014年比较,2017年( n = 28)尿中iAs%水平较低( Z =-2.87, P = 0.004),DMA%、PMI水平均较高( Z =-2.32、-2.87, P均< 0.05)。 结论:改水可以显著降低砷暴露人群尿砷代谢产物iAs、MMA、DMA、tAs水平,并升高其DMA%水平。
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abstractsObjective:To study the effect of water improvement on urinary arsenic methylation metabolism in population exposed to arsenic through drinking water.Methods:A cluster sampling method was used to select drinking water type arsenism areas in Bayannur City, Inner Mongolia Autonomous Region. Permanent residents lived in the arsenism areas for more than 10 years were selected as the survey subjects. Urine samples ( n = 874, 111, 145) were collected in 2004 (before water improvement), 2014 (4 years after water improvement) and 2017 (7 years after water improvement), respectively, and some subjects were followed up in 2014 and 2017. High performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) was used to detect different forms of arsenic metabolites in urine [inorganic arsenic (iAs), monomethylarsonic acid (MMA), dimethylarsenic acid (DMA)], and total arsenic (tAs), the iAs percentage (iAs%), MMA percentage (MMA%), DMA percentage (DMA%), monomethylation rate (PMI), dimethylation rate (SMI), and the ratio of MMA to DMA (MMA/DMA) were calculated. The content and distribution of urinary arsenic metabolites in people exposed to arsenic before and after water improvement were compared and analyzed. Results:Compared with 2004, the levels of iAs, MMA, DMA, tAs and iAs% in urine of arsenic exposed population in 2014 were lower ( Z =-14.12,-12.79,-14.27,-14.21,-6.90, P < 0.001), the levels of MMA%, DMA% and PMI were higher ( Z =-3.22,-2.91,-6.90, P < 0.05); in the same drinking water arsenic exposed population, compared with 2004, the levels of iAs, MMA, DMA, tAs and iAs% in urine ( n = 48) were lower ( Z =-5.57,-5.53,-5.54,-5.55,-2.86, P < 0.05) in 2014, and PMI level was higher ( Z =-2.86, P = 0.004). Compared with 2014, the levels of iAs% and MMA/DMA in urine of arsenic exposed population in 2017 were lower ( Z =-4.97,-2.25, P < 0.05), the levels of MMA, DMA, tAs, DMA%, PMI and SMI were higher ( Z =-4.01,-5.39,-4.77,-4.61,-4.97,-2.25, P < 0.05); in the same drinking water arsenic exposed population, compared with 2014, the level of iAs% in urine ( n = 28) was lower ( Z =-2.87, P = 0.004) in 2017, the levels of DMA% and PMI were higher ( Z =-2.32,-2.87, P < 0.05). Conclusion:Water improvement could significantly reduce the levels of urinary arsenic metabolites iAs, MMA, DMA and tAs and increase the level of DMA% in arsenic exposed population.
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